Effective removal of Pb(II) ions using piperazine-modified magnetic graphene oxide nanocomposite; optimization by response surface methodology

In this research, the piperazine-modified magnetic graphene oxide (Pip@MGO) nanocomposite was synthesized and utilized as a nano-adsorbent for the removal of Pb(II) ions from environmental water and wastewater samples. The physicochemical properties of Pip@MGO nanocomposite was characterized by X-ray diffraction analysis (XRD), Field emission scanning electron microscopy (FESEM), Transmission electron microscopy (TEM), Energy-dispersive X-ray spectroscopy (EDAX), Thermo-gravimetric analysis (TGA), Vibrating Sample Magnetometery (VSM) and Fourier-transform infrared spectroscopy (FT-IR) analysis. In this method, the batch removal process were designed by response surface methodology (RSM) based on a central composite design (CCD) model. The results indicated that the highest efficiency of Pb(II) removal was obtained from the quadratic model under optimum conditions of prominent parameters (initial pH 6.0, adsorbent dosage 7 mg, initial concentration of lead 15 mg L−1 and contact time 27.5 min). Adsorption data showed that lead ions uptake on Pip@MGO nanocomposite followed the Langmuir isotherm model equation and pseudo-second order kinetic model. High adsorption capacity (558.2 mg g−1) and easy magnetic separation capability showed that the synthesized Pip@MGO nanocomposite has great potential for the removal of Pb(II) ions from contaminated wastewaters.

www.nature.com/scientificreports/ USA) at room temperature in KBr pellets. Magnetic properties of produced nanocomposite were obtained by a vibrating sample magnetometer (VSM, MDKB model, Meghnatis Daghigh Kavir Co., Kashan, Iran). Thermogravimetric Analysis (TGA) was done using a TA Instruments analyzer (Q600, USA) by scanning to 800 °C with a heating rate of 10 °C min −1 . An ultrasonic water bath (ALEX, 8 L, power 170 W and frequency 32 kHz) was applied to disperse the of Pip@MGO nanocomposite adsorbent in the aqueous solutions. The pH adjustment of sample solutions were done with a Metrohm digital pH meter (632 model, Switzerland, Swiss) with a combined glass electrode.
Synthesis of Pip@MGO nanocomposite. Preparation of graphene oxide (GO). Graphene oxide (GO) was prepared according to Hummers' method with some modifications. Accordingly, 1.0 g of graphite powder was added to 50 mL of H 2 SO 4 (98%) in an ice bath. Afterwards, KMnO 4 (2 g) was added slowly. The addition should be in a way that the temperature does not exceed abruptly. After 2 h of stirring below 10 °C, and 1 h at 35 °C; 50 mL of deionized water was added. The mixture was heated at 85 °C for 1 h. Then 10 mL of H 2 O 2 (30%) was added in which the solution turned bright yellow. The mixture was filtered and was washed with HCl (5%) and deionized water for several times. Finally the obtained GO was dried at 60 °C in oven for 24 h 44 .
Preparation of magnetic graphene oxide (MGO). In a 250 mL round-bottom flask, 0.5 g of GO was added to deionized water (100 mL) and it was sonicated for 15 min. Subsequently, in another flask, FeCl 3 ·6H 2 O (1 g) and FeCl 2 ·4H 2 O (0.4 g) were mixed totally in deionized water (50 mL), for 1 h at 80 °C. The flask containing GO was added to the solution of Fe(III)/Fe(II) and then sonicated for 30 min in sonication bath. The mixture was heated to 80 °C and after 30 min, 15 mL of ammonia (30%) was added to it, resulted in MGO. The mixture was stirred for another 30 min and MGO was separated with an external magnet. The MGO was washed several times with deionized water and finally the obtained MGO was dried at 60 °C in oven for 24 h.
Preparation of piperazine modified magnetic graphene oxide (Pip@MGO). In a 100 mL round bottom flask, 0.5 g of MGO was added to 50 mL of toluene and the mixture was sonicated for 15 min. In another flask, 3-chloropropyltriethoxysilane (1 mmol, 0.24 g) and piperazine (1 mmol, 0.09 g) was premixed in 20 mL of toluene for 1 h at room-temperature. The latter flask was added to MGO containing flask and the mixture was refluxed for 24 h. Afterwards, Pip@MGO was separated with an external magnet and it was washed several times with ethanol. Finally, the collected Pip@MGO nanocomposite was dried at 60 °C in oven for 24 h and stored. A schematic representation of synthesis of Pip@MGO nanocomposite and its magnetic separation in adsorption processes was illustrated in Fig. 1 Table S1). Briefly, 10 mL of solution containing different concentrations of lead at a given pH (in the range of 5-7) was transferred to the test tubes and the known weight of adsorbent was added and sonicated in an ultrasonic bath for 2 min, then shacked (at 200 rpm) for a certain period of time, using an incubator shaker. After contact time, the liquid and solid phases were separated by an external magnet and the residual Pb 2+ concentration was measured by FAAS. The removal percentage (% R) and adsorption capacity of Pb(II) ions (q e ; mg g −1 ) were determined by the Eqs. (1) and (2): where C o is initial and C e is the final concentration of Pb(II) ions (mg L −1 ), V (L) is the volume of solution and M (mg) is the mass of adsorbent.
Experimental design. Response surface methodology (RSM) is a well-known and useful method that is widely used to optimize adsorption techniques and experimental design, modeling in chemical reactions and industrial processes 45 . In this work, the central composite design (CCD) under RSM was applied for designing the experiments. Therefore, the effect of four independent variables, including pH (in the range of 5-7), initial concentration of lead (in the range of 5-25 mg L −1 ), adsorbent dosage (in the range of 1-13 mg) and contact time (in the range of 2.5-52.5 min) on the Pb(II) removal efficiency (% R) were investigated. The statistical software Design Expert (Version 11.0.3.0), Stat-Ease, Inc. was applied to analyze the experimental data. As shown in Table 1, for four independent factors at 5 levels (− α, − 1, 0, 1, + α) thirty runs were designed, including six  Table S1). In this study, the proposed model was determined and confirmed by analysis of variance (ANOVA). In addition, R 2 , predicted R 2 , adjusted R 2 and F-test values were performed to evaluate and express the quality of the produced models.

Results and discussion
Characterization studies. In the FT-IR spectrum of the Pip@MGO (Fig. 2), the stretching vibration of C-H bonds of the graphene oxide (GO) is apparent in the 2928 cm −146 . The hydroxyl groups and also carboxylic groups on the surface of the GO is obvious at 3443 cm −1 . It should be mentioned that the Fe-O vibration is also seen at 580 cm −1 . The characteristic peaks located at 1635 cm −1 could be assigned to the bending vibration and stretching of -OH from the water molecules and structural hydroxyl groups 47 . The CH 2 bending vibration is located at 1456 cm −1 which can be attributed to the methylene groups of piperazine and also the propyl silane linker. The C=O stretching vibration of COOH groups on GO is observed at 1727 cm −148 . The Si-O-Si vibration of the siloxane appear about 1040 and 1117 cm −149 . The FT-IR spectrum of Pb-Adsorbed Pip@MGO (Pip@ MGO-Pb) was also recorded (Fig. 2). Thermogravimetric analysis (TGA) diagram of Pip@MGO is presented in Fig. 3. The first weight loss from room-temperature to 250 °C is due to the removal of adsorbed moisture entrapped physically in the nanocomposite. The second weight loss occurs from 250 to 800 °C which can be attributed to the breakdown of organic moieties from the nanocomposite. According to Fig. 4, the XRD pattern of the nanocomposite clearly shows the characteristic 2θ peaks of Fe 3 O 4 at 30.2°, 35.52°, 43.5°, 54, 57° and 63° are attributed to the crystal planes of magnetite at 220, 311, 400, 422, 511 and 440, respectively 50 .
The VSM curve of produced adsorbent is presented in Fig. 5. The results demonstrate that the nanocomposite contains magnetite nanoparticles which are super paramagnetic and the highest saturation magnetization is at 27.9 emu/g. It is apparent from the magnetization that the nanocomposite is sufficiently magnetic to be easily separable via an external magnet.
The SEM images ( Fig. 6) of the nanocomposite at two different magnifications has been recorded. According to SEM images, the layered character of the graphene oxide and also the magnetite nanoparticles are easily observed. The nanoparticles are agglomerated to some extent, but they have been distributed on the whole surface of the graphene oxide. The distribution of elements in the specified area by EDAX mapping has been shown in Fig. 7. It can be seen that nitrogen as a constituent of the piperazine group has been distributed uniformly all over the specific area which is an indication of the even functionalization of the whole surface without any accumulation. Furthermore the EDAX mapping of Pip@MGO-Pb was also recorded (Fig. 8). Figure 9 illustrates the results of energy-dispersive X-ray spectrum (EDAX) analysis of Pip@MGO. This data indicates the approximate chemical composition and confirms successful immobilization of piperazine which contains nitrogen. The iron is also present in the analysis due to the presence of Fe 3 O 4 nanoparticles in the nanocomposite. The results of energy-dispersive X-ray spectrum (EDAX) analysis of Pip@MGO-Pb is also presented in Fig. 10.
TEM images of the Pip@MGO nanocomposite is illustrated in Fig. 11. The layered 2D character of the graphene oxide is beautifully viewed in the TEM image which contains the magnetite nanoparticles located on its surface.
Suggested mechanisms of adsorption. In order to examine the mechanism of adsorption, the FT-IR and EDAX analysis of the lead (II)-adsorbed nanocomposite was recorded. From the general aspect, it can be Furthermore it can be concluded from the blank samples of GO and its comparison with piperazine functionalized GO, that piperazine functionalization has a synergistic effect in increasing adsroption. The EDAX analysis was also performed to evaluate lead ion adsorption. In the EDAX analysis (Fig. 10), it is apparent that the lead ions are far more widespread than nitrogen atoms of piperazine in EDAX mapping.  Optimization by RSM. To achieve maximum lead removal efficiency, the effect of four independent parameters including solution pH (A), Pb 2+ concentration (B), adsorption dosage (C) and shaking time (D) was performed via RSM design based CCD experiments. According to the obtained data, the quadratic model equation was used to describe the relationship between the removal efficiency (% R) and the effective parameters as well as the interaction of operating parameters. This model is expressed according to Eq. (1) as follows, in terms of coded factors: The ANOVA results for the removal efficiency of Pb(II) is summarized in Table 2. As shown, the F-value was 228.36 and p-value was less than 0.05 (p ˂ 0.0001), therefore implies that the quadratic model was statistically significant. Based on this concept (p ˂ 0.05) factors of A, B, C, D, AC, AD, BD, CD, A 2 , B 2 , C 2 and D 2 are significant model terms on removal efficiency of Pb(II) ions. In addition, the lack of fit p-value (0.2516) represented the LOF is not significantly relative to the pure error. The fit of proposed model was evaluated using coefficient of determination R 2 (0.9938) and adjusted R 2 (0.9895), which indicate a good relationship between the actual   Three-dimensional (3D) surface plots, which obtained using the CCD design, are given in Fig. 12. By applying these 3D diagrams, the simultaneous effects of independent parameters and their interaction on the removal efficiency can be investigated.
The initial pH value of the media is one of the most significant factors in the adsorption of metal ions 16 . As can be seen from Fig. 12a,b, the maximum removal efficiency of Pb(II) was achieved at pH 6.0. It can be explained that; at low pH values, due to presence of excessive amounts of H + ions in the solution, competition between Pb 2+ and H + occurs in the active sites on the adsorbent surface and repulsion of Pb 2+ and protonated amine 39 , as a result the removal efficiency decreases. However, at high pH values, despite the increase in deprotonation of adsorbent surface, Pb(II) ions are converted to hydroxide form and affect the absorption process, eventually reducing the removal efficiency 3,8 . Figure 12a,d shows that increasing the adsorbent dose increases the removal of ions, because it increases the number of adsorbent active sites and enhances the distribution coefficient of Pb(II) ions 4 . It is clear that, the optimum adsorbent dose for Pb 2+ removal is in the range of 6-8 mg of Pip@ MGO nanocomposite. At dose 7 mg, an equilibrium was achieved and on further addition of adsorbent dose percent removal of lead slightly decreased and it is supported by the fact that the active sites get overlapped on the nanoadsorbent surface due to overcrowding 51 .
The removal efficiency of the nanocomposite adsorbent used is affected by the contact time parameter due to the equilibrium nature of lead (II) removal. The results of Fig. 12b,d indicate that the removal efficiency increases with increasing contact time between lead ion and adsorbent, and after 25 min the removal percentage reaches more than 90%, and arrived at nearly constant amount at equilibrium conditions after this time. This variation in adsorption may be due to the relatively high concentration gradient and initially empty surface active sites. Later on at 25 min, the surface active sites get saturated with Pb 2+ ions and almost constant removal efficiency was acquired 52 .
The initial concentration of the metal ions in the solution is a key driving force in the adsorption of the ions into a solid phase. The effect of initial lead (II) concentration on removal efficiency is shown in Fig. 12c. As it is observed in the removal efficiency decreased on increasing lead (II) concentration. It can be deduced that at higher concentration levels, due to the saturation of the adsorbent active sites with lead ions, the adsorption did not change and the adsorption performance is decreased. Similar results were reported by Moradi et al. 8 , Dehghani et al. 53 and Bahrami et al. 54 . As a result of experimental investigations, in the concentration range of Adsorption isotherms study. In order to find the adsorption mechanism of lead ions on the Pip@MGO nanocomposite, the experimental data and homogeneity or heterogeneity of adsorbent were analysed by adsorption isothermal models. There are many isotherm models in the literature to describe the analyte adsorption on the adsorbents, however, in the present study, three conventional models including Freundlich, Langmuir and www.nature.com/scientificreports/ Temikin isotherm equations were used (see supplementary information for more details) [56][57][58][59] . For this purpose, in batch mode; 0.01 g of Pip@MGO nanocomposite was added to 10 mL of Pb 2+ solution with initial concentrations range of 50-600 mg L −1 , which was stabilized in pH = 6.0, and shacked (200 rpm) for 60 min at 25 °C. Subsequently, the magnetic adsorbent was isolated and the lead equilibrium concentration of each experiment was determined by FAAS, and the experimental data (Supplementary Table S2) were adjusted with the mentioned isotherm models. Supplementary Figure S1 reveals that upon adsorption equilibrium, the solid phase adsorbed amount of lead ions (Q e ) increased sharply with their aqueous concentration (C e ) in the low C e range. Such an increase became less significant at higher C e likely due to adsorbent saturation. As the initial Pb(II) aqueous concentration (C 0 ) increased from 50 to 600 mg L −1 , Q e increased from 64.3 to 525.7 mg g −1 . Since lead could be classified as a hard Lewis acid, the amine, hydroxyl and carboxyl groups (hard Lewis bases) on the adsorbent probably have a higher affinity for Pb 60 .
To describe the adsorption process, the considered isotherm was determined according to the correlation coefficient of the linear model of the common isotherm equations. Table 3 presents the correlation coefficients (R) and fitting model parameters of Langmuir, Freundlich and Temkin models. As can be seen, the Langmuir model's correlation coefficient (R = 0.998) is higher than 0.9 compared to other models. In addition, the maximum   Supplementary Fig. S2), the above result indicates that monolayer adsorption of Pb(II) occurred at homogeneous sites with equal energy on nanocomposite adsorbent 60 . Moreover, the maximum adsorption capacity (q max ) of Pip@MGO nanocomposite for Pb(II) reached 558.2 mg g −1 and it helps the fact that the proposed adsorbent has a high surface area, especially in the nano proportions. The results show that Pip@MGO is an effective adsorbent for removal of Pb 2+ .
Adsorption kinetics study. The kinetic study of the adsorption process provides information on the adsorption mechanism and how the Pb(II) ions are transferred from the liquid phase to the solid phase. Therefore, two kinetic models, including pseudo-first-order and pseudo-second-order equations were applied to fit the experimental data (see supplementary information for more details) 61,62 . These experiments were performed by shaking 0.01 g of Pip@MGO nanocomposite in 10 mL solution of 10 mg L −1 Pb(II) at pH 6 for 2, 3, 5, 10, 30 and 90 min. The results are presented in Supplementary Table S3. Table 4 summarizes the regression coefficients and kinetics parameters obtained from data review of the experimental results. According to the results, a good fit is represented by the pseudo-second-order model for the experimental kinetic data in terms of the correlation coefficient (R), because the value obtained for pseudosecond-order (R = 0.999) is greater than R (0.609) for the pseudo-first-order ( Supplementary Figs. S3 and S4). The rate-determining step is assumed to be chemisorption in the pseudo-second-order model, including valence forces by exchanging or sharing adsorbate and adsorbent electrons. In addition, the adsorption capacity is  www.nature.com/scientificreports/  Applications and reusability. In order to evaluate the application of the proposed method in the removing lead ions from real samples, three different water and wastewater samples, including Arvand Rud and Bahmanshir rivers, Persian Gulf seawater and petrochemical wastewater samples were investigated. To examine the effect of the sample matrices on the removal process, all samples were spiked by known concentrations of Pb(II) ions at two levels, 5 and 10 mg L −1 , subsequently the suggested method was performed under optimum conditions. The analysis results of each sample along with the recoveries are presented in Table 5. As can be seen, the removal efficiency of the lead ions in the studied samples were upper 93% which show well suitability of the developed nanocomposite adsorbent for removing of Pb(II) ions in various real samples. The regeneration cycles of Pip@MGO nanocomposite were carried out using acidic solution. The adsorption/ desorption study proved that the adsorbent with nitric acid (1 M) could be reused for four cycles. The results are shown in Supplementary Fig. S5. Based on this figure, the removal efficiency of Pip@MGO nanocomposite in four consecutive adsorption-regeneration cycles is more than 90%. After mentioned cycles, the removal efficiency of lead ions is reduced to less than 90%, and this can be attributed to the deformation of the absorbent material when used again or due to the saturation of the surface of the adsorbent 64,65 . These results show that Pip@MGO nanocomposite can be used multiple times, and the cost of adsorbent preparation can be reduced.

Comparison to methods in literature.
A comparative study of the analytical results of Pb(II) adsorption on the Pip@MGO nanocomposite with other adsorbents in the literature is reported in Table 6. From this table, it is obvious that Pip@MGO nanocomposite has a good adsorption capacity (mg g −1 ) for lead uptake compared to most mentioned adsorbents, while the adsorbent dosage used is less or comparable to other adsorbents.

Conclusions
In this present study, we have constructed a new magnetic graphene oxide-functionalized piperazine (Pip@ MGO) nanocomposite to remove Pb(II) ions from contaminated waters. The synthesized nanocomposite adsorbent was analyzed by using XRD, FESEM, TEM, EDAX, TGA, VSM and FT-IR techniques. The influence of four key parameters consisting initial pH, adsorbent dosage, initial concentration of lead and contact time on the removal efficiency were evaluated by RSM based on the central composite design (CCD) model. As a result of mathematical optimization, the maximum adsorption efficiency was obtained at pH 6.0, adsorbent dose of 7 mg, initial Pb 2+ concentration of 15 mg L −1 and contact time of 27.5 min.
The isotherm studies indicated that lead adsorption equilibrium data were more appropriate with Langmuir isotherm model. In addition, the obtained equilibrium data were applied to the kinetic equations and found to be consistent with the pseudo-second order model for lead adsorption. The suggested nanocomposite adsorbent represented good adsorption capacity and could be regenerated by nitric acid and reused for up to four adsorption-desorption cycles. According to our findings, the Pip@MGO nanocomposite as an effective adsorbent can